---
title: "Basic Graphical Displays"
output: 
  flexdashboard::flex_dashboard:
    theme:  
      version: 4
      bootswatch: cyborg
      navar-bg: "purple"
   
    orientation: columns
    vertical_layout: fill
    source_code: embed
    
    
---

```{r setup, include=FALSE}
library(flexdashboard)
library(DT)
library(tidyverse)
Friday<-read_csv("~/Downloads/Black_Friday.csv")
```
Brief Overview 1
===
Column {data-width=450}
---

In this session, we will use Black Friday Data in [Kaggle](https://www.kaggle.com/datasets/pranavuikey/black-friday-sales-eda) to study how to make the following graphical displays.

```{r}

```

Column {.tabset data-width=550}
-----------------------------------------------------------------------

### Graphical Displays
- Categorical Data
  - Bar Chart
  - Pie Chart
  

- Quantitative Data
  - Histogram
  - Box Plot
  - Scatter Plot
  - Line

### Common Arguments
- col: a vector of colors
- main: title for the plot
- xlim or ylim: limits for the x or y axis
- xlab or ylab: a label for the x axis
- font: font used for text, 1=plain; 2=bold; 3=italic; 4=bold italic

Brief Overview 2 {data-orientation=rows}
===

Row {data-height=100}
---
In this session, we will use Black Friday Data in [Kaggle](https://www.kaggle.com/datasets/pranavuikey/black-friday-sales-eda) to study how to make the following graphical displays.

Row {.tabset data-height=900}
---
### Graphical Displays
- Categorical Data
  - Bar Chart
  - Pie Chart
  

- Quantitative Data
  - Histogram
  - Box Plot
  - Scatter Plot
  - Line

### Common Arguments
Here is a list of common arguments:

- col: a vector of colors
- main: title for the plot
- xlim or ylim: limits for the x or y axis
- xlab or ylab: a label for the x axis
- font: font used for text, 1=plain; 2=bold; 3=italic; 4=bold italic

Data
=== 

Column {data-width=550}
---

### <b><font size = 4><span Style = "color:blue">First 500 Observations</span></font></b>

```{r show_table}
datatable(Friday[1:500,],rownames=FALSE, colnames = c("User ID", "Product ID", "Gender", "Age", "Occupation", "City Category", "Stay In Current City Years", "Marital Status", "Product Category 1", "Product Category 2", "Product Category 3", "Purchase"), options = list( pagelength = 20))


```

Column {data-width=450}
---

### <font size = 4><span Style = "color:red">Description</span></font>

In order to understand the customer purchases behavior against various products of different categories, the retail company "ABC Private Limited", in UK, shared purchase summary of various customers for selected high volume products from last month. The data contain the following variables.

- User_ID: User ID
- Product_ID: Product ID
- Gender: Sex of User
- Age: Age in bins
- Occupation: Occupation (masked)
- City_Category: Category of the City (A,B,C)
- Stay_In_Current_City_Years: Number of years stay in current city
- Marital_Status: Marital Status
- Product_Category: Product Category (Masked)
- Product_Category_2: Product may belongs to other category also (Masked)
- Product_Category_3: Product may belongs to other category also (Masked)
- Purchase: Purchase Amount